Test Cases for Regularized Optimization
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Updated
May 27, 2024 - Julia
Test Cases for Regularized Optimization
The Advanced Proximal Optimization Toolbox
Iterative shrinkage / thresholding algorithms (ISTAs) for linear inverse problems
Scientific Computational Imaging COde
A set of notebooks related to convex optimization, variational inference and numerical methods for signal processing, machine learning, deep learning, graph analysis, bayesian programming, statistics or astronomy.
Bazinga.jl: a toolbox for constrained composite optimization
PyProximal – Proximal Operators and Algorithms in Python
Nonconvex Exterior Point Operator Splitting
Self-concordant Smoothing for Large-Scale Convex Composite Optimization
Proximal Nested Sampling for high-dimensional Bayesian model selection
Official code repository for ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization (SIGGRAPH TOG 2023)
Proximal operators for use with RegularizedOptimization
Proximal algorithms for nonsmooth optimization in Julia
Proximal operators for nonsmooth optimization in Julia
A Matlab convex optimization toolbox using proximal splitting methods
Solving inverse problems with Proximal Markov Chain Monte Carlo
A Python convex optimization package using proximal splitting methods
Nonnegative Tensor Decomposition
Coordinate and Incremental Aggregated Optimization Algorithms
Repository for the MVA Optimization courses.
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